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Longitudinal Shoe Study: 2D Scan Images

dataset
posted on 03.02.2020 by Susan Vanderplas, Alicia Carriquiry, James Kruse, Guillermo Basulto-Elias, Stacy Renfro
Images of shoe prints from 160 pairs of shoes (“Nike Winflo 4” or “Adidas Seeley”; 4 sizes each) made using a 2D digital scanner (EverOS EverSpry) with associated measurements and data about shoe wear, surfaces, and wearers.

Each pair of shoes was worn for at least 10,000 steps per week over a 6-month period, with multiple measurements of the shoe soles taken initially and during three check-in periods spaced at approximately 5 week intervals.

The images are accompanied by 3 CSV files describing the shoes, visit (information collected from surveys along with the shoes), and individual images. The codebooks contain descriptions of the variables in each of the CSV files as well as a more extensive description of the file naming scheme outlined in the README.

These files can be used to examine wear pattern development, to look for the presence of identifying characteristics among shoes with similar features, and to develop algorithms for matching shoes based on individualizing characteristics.

Funding

ISU Funding: VPR Funds (290-17-04-16-1000)

National Institutes of Standards and Technology (426-17-02)

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